MODELLING THE IMPACT OF TRANSPORT PROCESSES ON OZONE WITH GEM-MARS: A COMPARISON WITH MARCI.
L. Neary, F. Daerden,Belgian Institute for Space Aeronomy, Brussels, Belgium, R. T. Clancy, M. J. Wolff,Space Science Institute, Boulder, Colorado, USA.
The composition of the Martian atmosphere is driven by a complex system of photochemistry, transport and small scale processes. Global Circulation Models (GCMs) are a crucial tool in the interpretation of observations, as has recently been shown by Clancy et al. (2012, 2013a), Bertaux et al. (2012), Federova et al. (2012) and Montmessin and Lef`evre (2013) for example. In anticipation of the ExoMars Trace Gas Orbiter (TGO) mission, the GEM-Mars model is used to analyse the photochemistry of the Martian atmosphere. Compar- isons are made with recent observations from the Mars Color Imager (MARCI) on the Mars Reconnaissance Orbiter (MRO) (Malin et al., 2001, Clancy et al., 2013) with some discussion regarding mixing in the free atmo- sphere and transport processes.
The chemical package included online in GEM-Mars uses reactions and rate coefficients based on the work of Garc`ıa-Mu˜noz et al. (2005). There are 15 photol- ysis and 31 chemical reactions (solved implicitly using Gaussian elimination method) and include the following 13 species: O3, O2, O(1D), O, CO, H, H2, OH, HO2, H2O, H2O2, O2(a1∆g) and CO2.
The chemical species are transported and mixed by the resolved circulation, eddy diffusion and in the upper atmosphere, molecular diffusion. Other physi- cal parameterisations included in the model are a 14 layer soil model with sub-surface ice, CO2 condensa- tion/sublimation and a water cycle with simple bulk con- densation. The simulations presented are made with hor- izontal resolution 4◦x4◦, 103 staggered vertical levels up to approximately 160 km, and a 30 minute timestep.
In the chemical scheme, ozone is produced by the following reaction:
and is destroyed by photolysis, reactions with O(1D) and most importantly, several reactions involving the products of H2O dissociation. Therefore, it is crucial to represent the water cycle correctly in the model as it is the driver for ozone. A comparison of GEM-Mars wa- ter vapour column with observations from the Thermal Emission Spectrometer (TES) (Smith, 2002) at 3 lati- tude bands is given in Figure 1. For the first half of the
year, the model compares well with the timing and mag- nitude of the water column, although the model slightly under-predicts at 60◦N. The second half of the year is during the dust storm season and the model over-predicts the column amounts by about 5 pr-µm. This version of GEM-Mars uses a prescribed dust scenario with a Con- rath profile shape which leads to warmer temperatures in the northern hemisphere during this time.
Transport also plays a role in the distribution of ozone as shown in Montmessin and Lef`evre (2013). Fig- ure 2 shows the zonal mean vertical distribution of ozone at Ls90◦from the model. A distinct layer can be seen at 60 km in the southern polar region which is a result of air containing extra oxygen being transported from lower latitudes to the polar night.
Comparison with MARCI
In Figure 3, the comparison of the zonally averaged day- time column ozone from GEM-Mars and MARCI shows that the overall pattern is represented by the model.
The maximums seen at high latitudes in fall, winter and spring are reproduced, but the mid-latitude values are slightly higher than observed. In the northern hemi- sphere spring between Ls30-60◦the MARCI data shows high column amounts around 60-70◦N. This maximum is not seen to be as strong in the model values. This may be a result of heterogeneous chemistry (not included in this version of the model) where HOxradical species re- act on the surface of ice particles, leading to less ozone destruction (as described in Lef`evre et al., 2008).
Model sensitivity studies showed that the free atmo- sphere stability functions and mixing length used can have a significant impact on the ozone column amount in the polar spring and summer. In the polar night within the vortex, there is very little mixing. In spring, around 60-70N latitude, planetary wave structures pro- duce strong variability at a given point, where air from inside and outside the vortex pass over (see Figure 4).
If there is little contrast in the mixing length inside and outside the vortex, the variability seen in the model is much lower. When the mixing length is lowered inside the vortex, the comparison is better, although still low (as expected, given the horizontal resolution of the sim- ulations). This is shown in Figure 5 with a time series of the ozone column from Ls0 to 26 at 70-74N latitude.
The model values are coloured by the ice optical depth to indicate that heterogeneous chemistry may also play
Figure 1: GEM-Mars water vapour column at 80N (top), 60N (centre) and 20N (bottom).
Figure 2: GEM-Mars zonal mean profile of ozone at Ls=90.
Figure 3: Comparison of GEM-Mars (top) and MARCI (bot- tom) zonal mean daytime column ozone.
Figure 4: GEM-Mars north polar snapshots of column ozone with wind field at∼25km at 4 times (Ls4-7◦). The red star is just to indicate one point for reference.
a role here.
As summer arrives, water vapour released from the polar cap is mixed upwards (and the HOx products of H2O photolysis), destroying ozone in the upper layer. If the free atmosphere mixing is too low, the water remains in the lower atmosphere and the decrease in column ozone is less (see Figure 6). The total column amount of water vapour does not change significantly, but it is the vertical distribution that is important in this case.
Discussion and conclusions
The GEM-Mars model is able to reproduce the basic features seen in the observations of ozone made by the MARCI instrument. In the north polar summer, when the water ice cap sublimates, mixing in the free atmo- sphere plays a role in the vertical distribution of water vapour and therefore the column amount of ozone.
Some processes are not included in the model version used for these results, including hetergeneous chem- istry, non-condensible gas-enrichment and interactive dust and clouds. The implementation of these processes is currently underway.
Figure 5: Time series from Ls=0-26◦at 70-74◦N latitude of ozone column as measured by MARCI (black circles) and simulated by GEM-Mars (markers coloured by GEM-Mars water ice extinction optical depth).
Figure 6: Time series from Ls=0-90◦at 70-74◦N latitude of ozone column as measured by MARCI (black circles) and simulated by GEM-Mars with different mixing lengths.
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